---
title: Pystackreg Web App
emoji: 🧠
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
tags:
  - image-processing
  - registration
  - pystackreg
---

# 🧠 Stack Image Registration Web App  
A web-based application for image stack registration powered by **Gradio** and **pystackreg**.  
This tool allows users to align and stabilize multi-frame TIFF images using a variety of transformation models.

<p align="center">
    <img src="https://raw.githubusercontent.com/qchapp/pystackreg-app/master/images/app.png" height="500">
</p>

---

## 🚀 Try the App  
The application is running on [Hugging Face](https://huggingface.co/), try it using this [link](https://huggingface.co/spaces/qchapp/pystackreg-app)!

---

## 🛠️ Installation  
We recommend performing the installation in a clean Python environment.

This app requires `python>=3.10`. To install dependencies, run:

```sh
pip install -r requirements.txt
```

---

## ▶️ Usage  
To run the app locally:

```sh
python app.py
```

Then open your browser and go to: [http://localhost:7860](http://localhost:7860)

---

## 🔍 About Stack Registration  
This app uses the [pystackreg](https://github.com/glichtner/pystackreg) library, a Python port of the TurboReg/StackReg algorithms.  
It supports several transformation models for alignment:
- Translation
- Rigid Body
- Scaled Rotation
- Affine
- Bilinear

---

## 📂 Features  
This application provides three core registration modes:

1. **📚 Reference-Based Alignment**  
   Align all frames within a stack to a selected reference frame — either from the same stack or an external 3D image.

2. **🎯 Stack-Based Alignment**  
   Align every frame in one stack to the first frame of another reference stack.

3. **🧩 Frame-to-Frame Alignment**  
   Align a single frame to another frame within the same stack.

By default, the app uses the **Rigid Body** transformation mode for all alignment tasks.  
If needed, users can enable **Advanced Settings** in each tab to select from other transformation models, such as Translation, Affine, or Bilinear.

Each mode offers:
- 🔍 Interactive image preview
- 🧭 Frame-by-frame navigation
- 💾 Downloadable aligned results
- ⚙️ Customizable transformation models via advanced options

---

### 📂 Examples in the App

You can try the application directly using preloaded examples from the [`pystackreg`](https://github.com/glichtner/pystackreg) repository.  
Each mode includes interactive buttons that load demo TIFF stacks automatically:

- 📚 **Reference-Based Alignment**:  
  Loads a stack of PC12 microscopy frames.

- 🎯 **Stack-Based Alignment**:  
  Loads both an unregistered and a translation-aligned stack.

- 🧩 **Frame-to-Frame Alignment**:  
  Uses the same unregistered stack for aligning specific frames.

No need to upload your own files — just click and experiment!

---

### 🌐 URL Parameter Support

The app supports loading image stacks from external URLs using query parameters.

**▶️ Load a single stack (for Reference-Based or Frame-to-Frame):**

```
https://huggingface.co/spaces/qchapp/pystackreg-app?file_url=https://github.com/glichtner/pystackreg/raw/master/examples/data/pc12-unreg.tif
```


**▶️ Load two stacks (for Stack-Based Alignment):**

```
https://huggingface.co/spaces/qchapp/pystackreg-app?file_url_1=https://github.com/glichtner/pystackreg/raw/master/examples/data/pc12-unreg.tif&file_url_2=https://github.com/glichtner/pystackreg/raw/master/examples/data/pc12-reg-translation.tif
```

> 💡 The app will automatically load and preview the provided stack(s) in the appropriate tabs.

---

## 🤖 MCP Server

This app doubles as a **Model Context Protocol (MCP) server**, exposing the three core registration workflows as callable MCP tools that any MCP-compatible client (e.g. Claude Desktop, GitHub Copilot in VS Code) can invoke programmatically.

### Running the app as an MCP server

```sh
python app.py
```

The human-facing Gradio UI is available at [http://localhost:7860](http://localhost:7860) as usual.  
The MCP endpoint is available at:

- **MCP server**: `http://localhost:7860/gradio_api/mcp/sse`
- **MCP schema**: `http://localhost:7860/gradio_api/mcp/schema`

### Available MCP tools

#### 1. `align_stack_to_reference`
Align every frame in a TIFF stack to a chosen reference frame (intra-stack alignment).

| Argument | Type | Default | Description |
|---|---|---|---|
| `stack_file` | `str` | — | Path to the input TIFF stack |
| `reference_index` | `int` | `0` | Zero-based index of the reference frame inside the stack |
| `mode` | `str` | `"RIGID_BODY"` | Transformation mode (see below) |
| `external_reference_file` | `str \| None` | `None` | Optional path to an external reference TIFF stack |
| `external_reference_index` | `int` | `0` | Frame index inside the external reference stack |

**Returns**: path to the aligned output TIFF file.

**Example arguments:**
```json
{
  "stack_file": "/data/pc12-unreg.tif",
  "reference_index": 0,
  "mode": "RIGID_BODY"
}
```

---

#### 2. `align_stack_to_stack`
Align every frame in a moving TIFF stack to the first frame of a reference TIFF stack.

| Argument | Type | Default | Description |
|---|---|---|---|
| `reference_stack_file` | `str` | — | Path to the reference TIFF stack |
| `moving_stack_file` | `str` | — | Path to the moving TIFF stack |
| `mode` | `str` | `"RIGID_BODY"` | Transformation mode (see below) |

**Returns**: path to the aligned output TIFF file.

**Example arguments:**
```json
{
  "reference_stack_file": "/data/pc12-unreg.tif",
  "moving_stack_file": "/data/pc12-reg-translation.tif",
  "mode": "TRANSLATION"
}
```

---

#### 3. `align_frame_to_frame`
Align a single moving frame to a reference frame within the same TIFF stack.

| Argument | Type | Default | Description |
|---|---|---|---|
| `stack_file` | `str` | — | Path to the TIFF stack containing both frames |
| `reference_index` | `int` | — | Zero-based index of the reference frame |
| `moving_index` | `int` | — | Zero-based index of the frame to align |
| `mode` | `str` | `"RIGID_BODY"` | Transformation mode (see below) |

**Returns**: path to the aligned single-frame output TIFF file.

**Example arguments:**
```json
{
  "stack_file": "/data/pc12-unreg.tif",
  "reference_index": 0,
  "moving_index": 5,
  "mode": "AFFINE"
}
```

---

### Supported transformation modes

| Mode | Description |
|---|---|
| `TRANSLATION` | Translation only (x/y shift) |
| `RIGID_BODY` | Translation + rotation (default) |
| `SCALED_ROTATION` | Translation + rotation + uniform scaling |
| `AFFINE` | Full affine transformation |
| `BILINEAR` | Bilinear (non-linear) transformation |

---

### 📚 Credits

- **App Author**: [Quentin Chappuis](https://github.com/qchapp)  
  Developed the Gradio-based web interface and integrated `pystackreg` for image stack registration.

- **Core Registration Library**: [pystackreg](https://github.com/glichtner/pystackreg)  
  A Python port of the StackReg plugin, written by [Gregor Lichtenberg](https://github.com/glichtner).

- **Original Algorithm Author**: Philippe Thévenaz (EPFL)  
  The core algorithm was originally developed by Philippe Thévenaz and is described in the following publication:

  > P. Thévenaz, U.E. Ruttimann, M. Unser.  
  > *A Pyramid Approach to Subpixel Registration Based on Intensity*.  
  > IEEE Transactions on Image Processing, vol. 7, no. 1, pp. 27–41, January 1998.  
  > [View paper](http://bigwww.epfl.ch/publications/thevenaz9801.html)

  For more information, visit the [Biomedical Imaging Group at EPFL](http://bigwww.epfl.ch/).

---